3D-MRI brain glioma intelligent segmentation based on improved 3D U-net network
The DSC, Recall, and Precision indices in the WT, TC, and ET segments using this method are the highest recorded, significantly enhancing glioma segmentation. This improvement bolsters the accuracy and reliability of diagnoses, ultimately providing a scientific foundation for clinical diagnosis and treatment.
Authors
- Tong Min Jiang (ORCID: https://orcid.org/0000-0002-9688-7886)
- Tingting Wang (ORCID: https://orcid.org/0000-0002-3648-4284)
- Tong Wu (ORCID: https://orcid.org/0000-0002-7468-2249)
- Ying Yan (ORCID: https://orcid.org/0000-0002-3546-3991)
- Hao Wang (ORCID: https://orcid.org/0000-0002-3424-6522)
- Shengnan Xu (ORCID: https://orcid.org/0000-0002-1791-4699)
- Defu Yang (ORCID: https://orcid.org/0000-0002-0212-9882)
- Qi Chen (ORCID: https://orcid.org/0000-0002-3621-8170)
- Ying Xu (ORCID: https://orcid.org/0000-0003-1452-8423)
- Baoguang Lin
- Dongyang Lv
Institutions
- General Hospital of Shenyang Military Region (CN)
Publication Details
- Journal
- PLoS ONE
- Published
- 2025-06-13
- DOI
- https://doi.org/10.1371/journal.pone.0325534
- Citations
- 3
- Primary Topic
- Brain Tumor Detection and Classification
- Type
- article
- Field-Weighted Citation Impact
- 2.53